}
initConfig(para)
#########################################################
startTime = time.clock() # start timing
logger.info('==============================================')
logger.info('Approach: HMF [He et al., ICWS\'2014].')
# load the dataset
dataMatrix = dataloader.load(para)
logger.info('Loading data done.')
# get the location groups for users as well as for services
locGroup = dataloader.getLocGroup(para)
logger.info('Clustering done.')
# run for each density
if para['parallelMode']: # run on multiple processes
pool = multiprocessing.Pool()
for density in para['density']:
pool.apply_async(evaluator.execute, (dataMatrix, locGroup, density, para))
pool.close()
pool.join()
else: # run on single processes
for density in para['density']:
evaluator.execute(dataMatrix, locGroup, density, para)
logger.info(time.strftime('All done. Total running time: %d-th day - %Hhour - %Mmin - %Ssec.',
time.gmtime(time.clock() - startTime)))
}
initConfig(para)
#########################################################
startTime = time.clock() # start timing
logger.info("==============================================")
logger.info("Approach: HMF [He et al., ICWS'2014].")
# load the dataset
dataMatrix = dataloader.load(para)
logger.info("Loading data done.")
# get the location groups for users as well as for services
locGroup = dataloader.getLocGroup(para)
logger.info("Clustering done.")
# run for each density
if para["parallelMode"]: # run on multiple processes
pool = multiprocessing.Pool()
for density in para["density"]:
pool.apply_async(evaluator.execute, (dataMatrix, locGroup, density, para))
pool.close()
pool.join()
else: # run on single processes
for density in para["density"]:
evaluator.execute(dataMatrix, locGroup, density, para)
logger.info(
time.strftime(
